Héctor Pérez Meana

Analysis of a wavelet-based watermarking algorithm

The analysis of a wavelet-based watermarking algorithm is presented, in which the discrete wavelet transform (DWT) is used for watermark embedding and detection. In the image compression field, the relationship between DWT coefficients and the human visual system (HVS) is researched intensively to get better compression performance. Recently, this knowledge has been applied to watermarking algorithms based in the DWT domain. The watermarking algorithm analyzed is adaptive to image characteristics, such as texture and luminance content, and it is realized using pixel by pixel masking in the DWT domain to embed the watermark with maximum energy. The detection process consists of cross-correlation between the marked image and pseudorandom sequences, and, in this process, the original image is not required. Computer simulation results show the robustness and perceptual invisibility of the algorithm.

Network forensics with Neurofuzzy techniques

Forensics science is based on a methodology composed by a group of stages, being the analysis one of them. Analysis is responsible to determine when a data constitutes evidence; and as a consequence it can be presented to a court. When the amount of data in a Network is small, its analysis is relatively simple, but when it is huge the data analysis becomes a challenge for the forensics expert. In this paper a forensics network model is proposed, which allows to obtain the existing evidence in an involved TCP/IP network. This Model uses the Fuzzy Logic and the Artificial Neural Networks to detect the Network flows that realize suspicious activities in the network or hosts, minimizing also the cost and the time to process the information in order to discriminate which are normal network flows and which has been subjected to attacks and intrusions.

Watermarking-based Color Image Authentication with Detection and Recovery Capability

In this paper a watermarking-based color image authentication with detection and recovery capability is proposed, in which a Halftone image is used as an approximated version of the luminance channel (Y) and a coded version of the coefficients of the Two Dimensional Discrete Cosine Transform of the chrominance channels (Cb, Cr) of the YCbCr color space are used as watermark signal. The luminance and chrominance information is embedded into the sub-bands of lowest frequency of the Integer Wavelet Transform of the original luminance channel using Quantization Index Modulation Dither Modulation. The luminance information in embedded into the LL sub-band meanwhile the chrominance information is embedded into the LH and HL sub-bands. Besides, a Multilayer Perceptron Neural Network is used as inverse halftoning to increase the quality of the recovered image. The experimental results show the effectiveness of the proposed method compared with some published before.

Wavelet image compression using universal coefficients matrix detail estimation

The paper represents a low complexity image compression algorithm by application of the two-dimensional discrete wavelet transform and the estimation of the detail matrices from the information matrix of the transformed image, using an adaptable RLS filter which estimates the detail matrices with universal coefficients. The reconstructed image is synthesized using the estimated detail matrices and information matrix provided by the wavelet transform.

Semi-Fragile Watermarking Based Image Authentication with Recovery Capability

In this paper, a block wise image authentication scheme using a semi-fragile watermark is proposed. The proposed scheme determines integrity of the image, detecting regions suffered some content modifications and altered region can be recovered without the original image. In the proposed scheme, the original image is divided into two regions: Region of Interest ROI, which is important region that requires protection against malicious modification and Region of Embedding ROE, which is the rest of the image where watermark sequence is embedded. The proposed scheme is evaluated from the several points of view: watermark imperceptibility, accuracy of tamper area detection, quality of recovered regions and robustness to nointentional manipulations, such as JPEG compression. Experimental results show excellent performance of the proposed scheme. Keywords-component; Image authentication; Semi-fragile watermark; recovery capability; self embedding

GMM vs SVM for Face Recognition and Face Verification

The security is a theme of active research in which the identification and verification identity of persons is one of the most fundamental aspects nowadays. Face recognition is emerging as one of the most suitable solutions to the demands of recognition of people. Face verification is a task of active research with many applications from the 80’s. It is perhaps the biometric method easier to understand and non-invasive system because for us the face is the most direct way to identify people and because the data acquisition method consist basically on to take a picture. Doing this recognition method be very popular among most of the biometric systems users. Several face recognition algorithms have been proposed, which achieve recognition rates higher than 90% under desirable’s condition (Chellapa et al., 2010; Hazem & Mastorakis, 2009; Jain et al., 2004; Zhao et al., 2003). The recognition is a very complex task for the human brain without a concrete explanation. We can recognize thousands of faces learned throughout our lives and identify familiar faces at first sight even after several years of separation. For this reason, the Face Recognition is an active field of research which has different applications. There are several reasons for the recent increased interest in face recognition, including rising public concern for security, the need for identity verification in the digital world and the need for face analysis and modeling techniques in multimedia data management and computer entertainment. Recent advances in automated face analysis, pattern recognition, and machine learning have made it possible to develop automatic face recognition systems to address these applications (Duda et al., 2001). This chapter presents a performance evaluation of two widely used classifiers such as Gaussian Mixture Model (GMM) and Support Vector Machine (SVM) for classification task in a face recognition system, but before beginning to explain about the classification stage it is necessary to explain with detail the different stages that make up a face recognition system in general, to understand the background before using the classifier, because the stages that precede it are very important for the proper operation of any type of classifier.

Robust watermarking based on histogram modification

In this paper, a robust watermarking method against geometric distortions and common signal processing is proposed. This method is based on two modifications in the 2D histograms. In the first modification, a selected region of 2D histogram composed by R-G color components is modified according to the watermark pattern. In the second modification, another 2D histogram composed by B component and image feature is dynamically partitioned to embed the watermark pattern. The experimental results show robustness against several geometric distortions, common signal processing attacks and some combination attacks. Also the comparison with the prior methods shows the better performance of the proposed method.

Real-Time Audio Watermarking System Prototype

A real-time audio watermarking system is presented. System contains two circuits: the marker circuit and the detector circuit. Watermark detection is blind, so, there is no necessary original signal to detect embedded information. Watermark detection does not need a synchronization stage; therefore, detection is carried out on any time. Both, marker and detector are implemented in a commercial digital signal processor starter kit from Texas Instruments and are fully host-independent

New Condition for Hierarchical Secret Image Sharing Scheme

Recently hierarchical threshold secret image sharing (SIS) scheme was proposed to provide hierarchical access structures to the conventional SIS. These hierarchical access structures are more adequate than the conventional SIS in many practical situations. However in the actual hierarchical SIS scheme, even if the access condition is not satisfied, the secret image is visually leaked, which is very serious security deficiency of this SIS scheme. The present work proposes a new condition for the hierarchical threshold SIS scheme to guarantee the secrecy of the secret image when the access condition is not satisfied. The experimental results show the functionality of the SIS with the proposed condition, in which if the access condition is satisfied then the secret image is recovered in lossless manner, otherwise only pseudorandom pattern is extracted.

Rational Dither Modulation in audio signals

A data hiding system based in Rational Dither Modulation is proposed. This system hides information into the audio signals in Modulated Complex Lapped Transform (MCLT) domain. The system proposed is able to hide around of 43 bits per second in a CD-quality audio signal. Objective and subjective evaluations show robustness to classical attacks and transparency to Human Auditory System (HAS), respectively.